基于干扰观测器的轮廓误差耦合控制研究

针对多轴运动的轮廓误差，提出了基于干扰观测器的轮廓误差耦合控制。该方法通过构造干扰观测器来预测各单轴系统的内部和外部干扰，并根据预测到的干扰信息对各轴进行补偿以消除干扰对系统的影响。考虑到系统的动态特性，拟采用模糊神经网络对干扰信号进行动态分配，并依据轮廓误差耦合控制思想补偿到各轴，达到轮廓误差最小控制。而文章采用遗传算法对网络进行训练以加快网络训练速度，且不易陷入局部最小。仿真结果证明其可行性与有效性。

Cross-coupling Control Research of Contour Error Basedon Disturbance Observer

In order to reduce the contour error of multi-axis motion system, a novel cross-coupling control method based-on disturbance observer is proposed in this paper. That is, through estimation of the internal and external disturbance of each axis by using disturbance observer, the disturbance acting on each axis can be compensated, and then the effect of disturbance is suppressed. Considering the dynamic property, the fuzzy neural network is used to distribute the disturbance dynamically and this additional information is compensated to each axis according to system contour error. Furthermore this paper uses GA (Genetic Algorithm) as the training algorithm of fuzzy neural network, which has the advantage of fast convergence and will not converge at local nadir. Simulation results demonstrate that the algorithm is feasible and valid.